Wireless systems transmit communication signals in the downlink over radio frequency channels from a radio device, for example a fixed transceiver such as a base station, to another radio device, for example a user equipment (UE), within a geographic area, or cell. The UE may transmit signals in the uplink to one or more base stations. In both cases, the received signal may be characterized as the transmitted signal, altered by channel effects, plus noise and interference. To recover the transmitted signal from a received signal, a receiver thus requires both an estimate of the channel, and an estimate of the noise/interference. The characterization of a channel is known as channel state information (CSI). One known way to estimate a channel is to periodically transmit known reference symbols, also known as pilot symbols. Since the reference symbols are known by the receiver, any deviation in the received symbols from the reference symbols (once estimated noise/interference is removed) is caused by channel effects. An accurate estimate of CSI allows a receiver to more accurately recover transmitted signals from received signals. In addition, by transmitting CSI from the receiver to a transmitter, the transmitter may select the transmission characteristics—such as coding, modulation, and the like—best suited for the current radio channel condition. This is known as channel-dependent link adaptation.
Multiple-input, multiple-output (MIMO) communications can significantly increase spectral efficiencies of wireless systems. Under idealized conditions, a capacity scales as the minimum of (nr, nt) where nr is the number of receive antennas and nt is the number of transmit antennas. The possibility of high data rates has spurred work on the capacity achievable by MIMO systems under various assumptions about the channel, the transmitter and the receiver. The spatial channel model and assumptions about the channel state information (CSI) at the transmitter (CSIT) and the receiver (CSIR) have a significant impact on the MIMO capacity.
Various data symbol transmission techniques have been proposed for MIMO systems, e.g. in the context of a single-carrier system with a flat fading radio channel. In the particular circumstance of a flat fading channel, the propagation channel between any one antenna of the transmitter and any one antenna of the receiver may be modeled by means of a complex gain. As a result, the propagation channel between a transmitter having a plurality of transmit antennas and a receiver having a plurality of receive antennas can be written in the form of a complex matrix, referred to as the MIMO propagation channel matrix, in which each row corresponds to a receive antenna and each column corresponds to a transmit antenna.
Among those techniques, some rely on knowledge of the MIMO propagation channel matrix on transmission. This channel knowledge makes it possible to calculate a focusing or “beamforming” matrix Q that is applied to the data symbols before they are transmitted by the transmit antennas. This precoding matrix Q enables each data symbol to be focused on a particular receive antenna in order to facilitate decoding of the received data symbols on reception.
Furthermore a radio device such as a base station BS, when having excessive number of antennas, can simultaneously schedule multiple receivers at the same time/frequency band with simple linear processing such as maximum-ratio transmission (MRT) or zero-forcing (ZF) in the downlink and maximum-ratio combining (MRC) or ZF in the uplink. This is often referred to as very large (VL) multi-user (MU) multiple-input-multiple-output (MIMO) or massive MIMO and is abbreviated by VL-MIMO or Massive-MIMO hereafter.